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Cryptocurrencies like Bitcoin are increasingly attracting millions of users, but also cybercriminals, as a successful attack means maximum profit with little risk. This also applies to "ether," the most widely used cryptocurrency after Bitcoin. As a precautionary measure, researchers at the CISPA Helmholtz Center i.G. at Saarland University have developed a methodology for this cryptocurrency that not only finds security vulnerabilities, but also uses them to automatically develop attacks. The result: they found 815 security holes that allow 1564 attacks. The Saarbrucken computer scientists present their approach on Wednesday at the international USENIX Security Symposium in Baltimore, USA.

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Digital data is considered the "new oil" in business and industry as it promises the same profits as the oil business. An entire industry is already based on "data science" and computational methods that promise even better analysis to outperform competitors and to find future business opportunities. So that the "new oil" does not turn out to be a false promise for customers, four renowned computer science experts of Saarland University are now founding the consulting firm "D:AI:MOND". Their "Data Science Consulting" is based on the latest research findings. In this way, the scientists want to provide their customers with sound advice.

"Big Data", the analysis of huge amounts of data, "Artificial Intelligence" and "Deep Learning" are the processes that are currently causing a sensation in the economy. "The confusion in the industry regarding all these trendy terms is unfortunately very large," explains Jens Dittrich, professor of computer science in the field of databases, data management and big data at Saarland University. "As a researcher, we can clear this fog," Dittrich is convinced. Hence, together with his colleague Verena Wolf, a professor of computer science with a focus on modeling and simulation, and the two computer science experts Endre Palatinus and Thilo Krüger, he is founding the start-up "D:AI:MOND".

A big problem, according to Dittrich, is that some companies misjudge the data analysis process. He compares their approach with the construction of a penthouse on the tenth floor, without planning the floors below or even the foundation. "Another pattern we see is that some companies believe it will be a very large building, so first they buy a costly special excavator. Only then is the building planned and they realize that even a simple excavator would have been enough."

In addition, says Dittrich, data analysis requires much more than just evaluation. Collecting the right data, cleaning and merging the data are just as important as removing errors, maintaining the data, setting up a scalable data architecture, and defining the characteristics critical to analysis, Dittrich explains.

His start-up D:AI:MOND is supported by the on-campus IT Incubator, an institution of Saarland University and Max Planck Innovation GmbH. During the so-called incubation phase, researchers and students receive help there to develop their ideas entrepreneurially.